DEEP LEARNING FOR BIOMEDICINE APPLICATIONS

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Bouhafra, S., & El Bahi, H. (2025). Deep Learning Approaches for Brain Tumor Detection and Classification Using MRI Images (2020 to 2024): A Systematic Review. Journal of Imaging Informatics in Medicine, 38(3), 1403–1433.

Buda, M., Saha, A., & Mazurowski, M. A. (2019). Association of Genomic Subtypes of Lower-Grade Gliomas with Shape Features Automatically Extracted by a Deep Learning Algorithm. Computers in Biology and Medicine, 109, 218–225.

Chattopadhay, A., Sarkar, A., Howlader, P., & Balasubramanian, V. N. (2018). Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks. Dalam IEEE Winter Conference on Applications of Computer Vision (WACV), hlm. 839–847.

Chen, X., Wang, X., Zhang, K., Fung, K. M., Thai, T. C., Moore, K., Mannel, R. S., Liu, H., Zheng, B., & Qiu, Y. (2021). Recent Advances and Clinical Applications of Deep Learning in Medical Image Analysis. Medical Image Analysis, 79, 102444.

Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2021). A Guide to Deep Learning in Healthcare. Nature Medicine, 27(1), 29–41.

He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep Residual Learning for Image Recognition. Dalam Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), hlm. 770–778.

Horbinski, C., Berger, T., Packer, R. J., & Wen, P. Y. (2022). Clinical Implications of the 2021 Edition of the WHO Classification of Central Nervous System Tumours. Nature Reviews Neurology, 18(9), 515–529.

Islam, M. R., dkk. (2022). Transfer Learning Based Pneumonia Detection from Chest X-ray Images Using EfficientNet. Journal of Medical Imaging and Health Informatics.

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Li, M., Jiang, Y., Zhang, Y., & Zhu, H. (2023). Medical Image Analysis Using Deep Learning Algorithms. Frontiers in Public Health, 11, 1273253.

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Makwana, C. (2024). Automated Segmentation of Brain Tumors in MRI: A Comprehensive Review of Deep Learning Approaches. Journal of Electrical Systems, 20(7s), 1942–1948.

Milletari, F., Navab, N., & Ahmadi, S. A. (2016). V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation. Dalam Fourth International Conference on 3D Vision (3DV), hlm. 565–571.

Oktay, O., Schlemper, J., Le Folgoc, L., Lee, M., Heinrich, M., Misawa, K., Mori, K., McDonagh, S., Hammerla, N. Y., Kainz, B., Glocker, B., & Rueckert, D. (2018). Attention U-Net: Learning Where to Look for the Pancreas. Dalam Medical Imaging with Deep Learning (MIDL).

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Selvaraju, R. R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., & Batra, D. (2017). Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization. Dalam Proceedings of the IEEE International Conference on Computer Vision (ICCV), hlm. 618–626.

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Tan, M., & Le, Q. V. (2019). EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. Dalam Proceedings of the 36th International Conference on Machine Learning (ICML), hlm. 6105–6114.

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Zhou, Z., Rahman Siddiquee, M. M., Tajbakhsh, N., & Liang, J. (2018). UNet++: A Nested U-Net Architecture for Medical Image Segmentation. Dalam Deep Learning in Medical Image Analysis (DLMIA), hlm. 3–11.